A tool for VCF files diagnostics
- Input VCF file can be compressed (.gz) and uncompressed
- Tool adapted to work with multi-individual VCF and with VCF of only one individual
- Positions of the VCF can be SNPs, INDELS or ROHs
- Can filter the VCF by sample depth, mapping quality and missing data by SNP
- Can generate distribution plots of the missing data by SNP, the reference allele frequency and the sample depth by individual
- Can generate distribution plot of missing data by population, perform a PCA, test the Hardy-Weinberg equilibrium and generate the distribution plot of the inbreeding coefficient, if the VCF is multi-individual and the list of individuals and its populations is uploaded
- It allows to download the filtered VCF and the plots
- Create virtual environment:
conda create --name vcfcheck-app python=3.7
- Activate virtual environment:
source vcfcheck-app/bin/activate
or
conda activate vcfcheck-app
- Install dependencies:
pip install -r requirements.txt
- Activate virtual environment:
source vcfcheck-app/bin/activate
or
conda activate vcfcheck-app
- Execute program:
python VCFcheck.py
- Copy url on the web browser (http://0.0.0.0:8050/)
deactivate
As input, the software requires a (compressed or uncompressed) VCF file:
##fileformat=VCFv4.2
##FILTER=<ID=PASS,Description="All filters passed">
##contig=<ID=1,length=315321322>
##contig=<ID=2,length=162569375>
##ALT=<ID=X,Description="Represents allele(s) other than observed.">
##INFO=<ID=INDEL,Number=0,Type=Flag,Description="Indicates that the variant is an INDEL.">
##INFO=<ID=IDV,Number=1,Type=Integer,Description="Maximum number of reads supporting an indel">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Raw read depth">
##FORMAT=<ID=PL,Number=G,Type=Integer,Description="List of Phred-scaled genotype likelihoods">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Number of high-quality bases">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##INFO=<ID=MQ,Number=1,Type=Integer,Description="Average mapping quality">
##INFO=<ID=END,Number=1,Type=Integer,Description="End position of the variant described in this record">
##FILTER=<ID=LOWQUAL,Description="Set if true: %QUAL<10 || %MAX(DP)<5 || %MAX(DP)>15">
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT IBGU1330
1 4040059 . T . . PASS END=4040089 GT 0/0
1 4624048 . T . . PASS END=4624079 GT 0/0
1 7900743 . G . . PASS END=7900743 GT 0/0
1 14739858 . A . . PASS END=14739886 GT 0/0
1 15676648 . T . . PASS END=15676649 GT 0/0
1 17520198 . G . . PASS END=17520206 GT 0/0
1 19562975 . A . . PASS END=19563008 GT 0/0
1 21407709 . A T 118 PASS DP=7;VDB=0.788273;SGB=-0.590765;MQSB=0.5;MQ0F=0;AC=2;AN=2;DP4=0,0,2,3;MQ=53 GT:PL:DP 1/1:145,15,0:5
1 22086814 . A G 177 PASS DP=7;VDB=0.86172;SGB=-0.636426;MQSB=1;MQ0F=0;AC=2;AN=2;DP4=0,0,5,2;MQ=60 GT:PL:DP 1/1:204,21,0:7
As optional input, it is possible to upload a file with all the samples in a column and another column with the populations to which each sample belongs (separated by tab).
SAMPLE1 POP1
SAMPLE2 POP1
SAMPLE3 POP1
SAMPLE4 POP1
SAMPLE5 POP2
SAMPLE6 POP2
SAMPLE7 POP2
SAMPLE8 POP3
SAMPLE9 POP3
SAMPLE10 POP3
SAMPLE11 POP3
When the inputs are uploaded, the type of mutations to analyze must be selected before starting the analysis.
Then, the table from the VCF and a summary (with warnings about possible biases in the VCF) will be displayed. In that moment, it is possible to filter the file by sample depth, mapping quality or missing data using the corresponding sliders.
Once the table is generated, we can perform different plots and analysis by its selection in the dropdown and download the filtered VCF or the summary using the corresponding buttons.
